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EPIA
2003
Springer

Border Detection on Remote Sensing Satellite Data Using Self-Organizing Maps

10 years 4 months ago
Border Detection on Remote Sensing Satellite Data Using Self-Organizing Maps
In this paper, a new approach to Mediterranean Water Eddy border detection is proposed. Kohonen self-organizing maps (SOM) are used as data mining tools to cluster image pixels through an unsupervised process. The clusters are visualized on the SOM internal map. From the visualization, the borders can be detected through an interactive way. As a result, interesting patterns are visible on the images. The proposed SOM approach is tested on Atlantic Ocean satellite data and compared with conventional gradient edge detectors. Keywords remote sensing satellite data, border detection, self-organizing map (SOM), clustering, gradient edge detector
Nuno M. C. Marques, Ning Chen
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where EPIA
Authors Nuno M. C. Marques, Ning Chen
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